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X Demographics
Mendeley readers
Attention Score in Context
Title |
Accelerated large-scale multiple sequence alignment
|
---|---|
Published in |
BMC Bioinformatics, December 2011
|
DOI | 10.1186/1471-2105-12-466 |
Pubmed ID | |
Authors |
Scott Lloyd, Quinn O Snell |
Abstract |
Multiple sequence alignment (MSA) is a fundamental analysis method used in bioinformatics and many comparative genomic applications. Prior MSA acceleration attempts with reconfigurable computing have only addressed the first stage of progressive alignment and consequently exhibit performance limitations according to Amdahl's Law. This work is the first known to accelerate the third stage of progressive alignment on reconfigurable hardware. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 3 | 6% |
Spain | 3 | 6% |
Brazil | 2 | 4% |
Sweden | 2 | 4% |
Colombia | 1 | 2% |
Australia | 1 | 2% |
United States | 1 | 2% |
Unknown | 36 | 73% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 15 | 31% |
Student > Ph. D. Student | 11 | 22% |
Student > Master | 5 | 10% |
Professor | 4 | 8% |
Student > Postgraduate | 4 | 8% |
Other | 10 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 24 | 49% |
Computer Science | 10 | 20% |
Engineering | 5 | 10% |
Biochemistry, Genetics and Molecular Biology | 3 | 6% |
Mathematics | 2 | 4% |
Other | 2 | 4% |
Unknown | 3 | 6% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 December 2011.
All research outputs
#18,587,406
of 23,023,224 outputs
Outputs from BMC Bioinformatics
#6,352
of 7,316 outputs
Outputs of similar age
#197,327
of 242,326 outputs
Outputs of similar age from BMC Bioinformatics
#89
of 103 outputs
Altmetric has tracked 23,023,224 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,316 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 5th percentile – i.e., 5% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 242,326 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 103 others from the same source and published within six weeks on either side of this one. This one is in the 2nd percentile – i.e., 2% of its contemporaries scored the same or lower than it.